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20182023
most citedSummarising Historical Text in Modern Languages

13 citations · 45 across the 12 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL2023★ 3 cited

Dual-Gated Fusion with Prefix-Tuning for Multi-Modal Relation Extraction

Qian Li, Shu Guo, Cheng Ji +3

Multi-Modal Relation Extraction (MMRE) aims at identifying the relation between two entities in texts that contain visual clues. Rich visual content is valuable for the MMRE task,…

cs.CL2022★ 5 cited

On the Security Vulnerabilities of Text-to-SQL Models

Xutan Peng, Yipeng Zhang, Jingfeng Yang +1

Although it has been demonstrated that Natural Language Processing (NLP) algorithms are vulnerable to deliberate attacks, the question of whether such weaknesses can lead to softwa…

cs.CL2021★ 3 cited

Generating Disentangled Arguments with Prompts: A Simple Event Extraction Framework that Works

Jinghui Si, Xutan Peng, Chen Li +2

Event Extraction bridges the gap between text and event signals. Based on the assumption of trigger-argument dependency, existing approaches have achieved state-of-the-art performa…

cs.CL2021★ 8 cited

Cross-Lingual Word Embedding Refinement by Norm Optimisation

Xutan Peng, Chenghua Lin, Mark Stevenson

Cross-Lingual Word Embeddings (CLWEs) encode words from two or more languages in a shared high-dimensional space in which vectors representing words with similar meaning (regardles…

cs.CL2021★ 13 cited

Summarising Historical Text in Modern Languages

Xutan Peng, Yi Zheng, Chenghua Lin +1

We introduce the task of historical text summarisation, where documents in historical forms of a language are summarised in the corresponding modern language. This is a fundamental…

cs.CL2020★ 1 cited

Understanding Linearity of Cross-Lingual Word Embedding Mappings

Xutan Peng, Mark Stevenson, Chenghua Lin +1

The technique of Cross-Lingual Word Embedding (CLWE) plays a fundamental role in tackling Natural Language Processing challenges for low-resource languages. Its dominant approaches…